Immigration and neoliberalism: three cases and counter accounts
Bibliographic record
Abstract
Purpose – This paper advocates for critical accounting’s contribution to immigration deliberations as part of its agenda for advancing social justice. The purpose of this paper is to illustrate accounting as implicated in immigration policies of three advanced economies. Design/methodology/approach – The authors suggest that neoliberal immigration policies are operationalized through the responsibilization of individuals, corporations and universities. By examining three immigration policies from the USA, Canada and the UK, the paper clarifies how accounting technologies facilitate responsibilization techniques, making immigration governable. Additionally, by employing immigrant narratives as counter accounts, the impacts of immigrant lived experiences can be witnessed. Findings – Accounting upholds neoliberal principles of life by expanding market mentalities and governance, through technologies of measurement, reports, audits and surveillance. A neoliberal strategy of responsibilization contributes to divesting authority for immigration policy in an attempt to erase the social and moral agency of immigrants, with accounting integral to this process. However the social cannot be eradicated as the work illustrates in the narratives and counter accounts that immigrants create. Research limitations/implications – The work reveals the illusion of accounting as neutral. As no single story captures the nuances and complexities of immigration practices, further exploration is encouraged. Originality/value – The work is a unique contribution to the underdeveloped study of immigration in critical accounting. By unmasking accounting’s role and revealing techniques underpinning immigration discourses, enhanced ways of researching immigration are possible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.024 | 0.039 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".